Abstract
With the rapid advancements in cancer research, the information that is useful for characterizing disease, staging tumors, and creating treatment and survivorship plans has been changing at a pace that creates challenges when physicians try to remain current. One example involves increasing usage of biomarkers when characterizing the pathologic prognostic stage of a breast tumor. We present our semantic technology approach to support cancer characterization and demonstrate it in our end-to-end prototype system that collects the newest breast cancer staging criteria from authoritative oncology manuals to construct an ontology for breast cancer. Using a tool we developed that utilizes this ontology, physician-facing applications can be used to quickly stage a new patient to support identifying risks, treatment options, and monitoring plans based on authoritative and best practice guidelines. Physicians can also re-stage existing patients or patient populations, allowing them to find patients whose stage has changed in a given patient cohort. As new guidelines emerge, using our proposed mechanism, which is grounded by semantic technologies for ingesting new data from staging manuals, we have created an enriched cancer staging ontology that integrates relevant data from several sources with very little human intervention.
Abstract (translated)
随着癌症研究的快速发展,有助于表征疾病,分期肿瘤,制定治疗和生存计划的信息正在以一种速度发生变化,这在医生试图保持现状时会带来挑战。一个例子涉及在表征乳腺肿瘤的病理预后阶段时增加生物标志物的使用。我们提出了我们的语义技术方法来支持癌症表征,并在我们的端到端原型系统中展示它,该系统从权威肿瘤学手册收集最新的乳腺癌分期标准,以构建乳腺癌的本体论。使用我们开发的利用此本体的工具,面向医生的应用程序可用于快速安排新患者,以支持基于权威和最佳实践指南识别风险,治疗选项和监控计划。医生还可以重新安排现有患者或患者群体,使他们能够找到在给定患者队列中阶段发生变化的患者。随着新指南的出现,使用我们提出的机制,该机制以语义技术为基础,从分期手册中提取新数据,我们创建了一个丰富的癌症分期本体,集成了来自多个来源的相关数据,几乎没有人为干预。
URL
https://arxiv.org/abs/1807.07991